Data Structures and Algorithms. Chapter 1

Transcription

1 Data Structures Dr Ahmed Rafat Abas Computer Science Dept, Faculty of Computer and Information, Zagazig University

2 Data Structures and Algorithms Chapter 1

3 1.1 A Philosophy of Data Structures The need for Data Structures Representing information is fundamental to computer science. The majority of computer programs stores and retrieves information. To be practical in terms of storage space and running time, these programs should organize their information in a way that supports efficient processing. Therefore, the study of data structures and the algorithms that manipulate them is at the heart of computer science.

4 What is meant by a data structure? A data structure is a data representation and its associated operations. Examples: integer numbers, floating point numbers, arrays of these numbers.

5 1.1.2 Costs and Benefits Each data structure has associated costs and benefits. A data structure requires a certain amount of space for each data item it stores, time to perform a single basic operation, programming effort. Each problem has constraints on available space and time. The best data structure for a problem is the one that allows the computer program to solve the problem efficiently in terms of the required storage and time.

6 1.2 Abstract Data Types and Data Structures Definitions: A Type is a collection of values. For example, the Boolean type consists of the values True and False. A Data type is a type together with a collection of operations to manipulate the type. For example, an integer variable is a member of the integer data type.

7 A Data item is a piece of information or a record whose value is drawn from a type. An Aggregate data item is a complex data item that contains many data items, probably their values are drawn from different data types.

8 An Abstract data type (ADT) defines a data type in terms of a type and a set of operations on that type. Each operation is defined by its inputs and outputs. An ADT definition does not specify how the data type is implemented. Encapsulation is the process of hiding implementation details.

9 A Data structure is the physical implementation of an ADT. Each operation associated with the ADT is implemented by one or more subroutines. The term data structure often refers to data stored in a computer's main memory. Example: the mathematical concept of integer, along with operations that manipulate integers, form an ADT. The C++ int variable type is a physical representation of the abstract integer.

10 A File structure refers to the organization of data on peripheral storage, such as a disk drive or magnetic tape. Data items have both a logical and a physical form. The definition of the data item by an ADT is its logical form, the implementation of the data item within a data structure is its physical form

11 Data Type ADT Type Operations Data item Logical form Data structure Storage Subroutines Data item Physical form The relationship between data item, ADT and data structure. The ADT defines the logical form of the data type, while the data structure implements the physical form of the data type.

12 1.3 Problems, Algorithms and Programs Definitions A Problem is a task to be performed. It is best thought of as inputs and corresponding outputs. A problem definition should include constraints on the resources that may be used by an acceptable solution but it should not include any constraints on how the problem should be solved.

13 A Function is a matching between inputs (the domain) and outputs (the range). Values of the inputs are called the parameters of the function. Therefore, all problems are functions according to this definition.

14 An Algorithm is a method or a process adopted in order to solve a problem. The algorithm takes the inputs of a certain problem and transforms them to the corresponding outputs of this problem. It is possible to find several different algorithms that can solve a certain problem. Example: a certain sorting algorithm may be preferred for small sets of numbers while another algorithm may be preferred for large sets of numbers.

15 A Program is an instance of an algorithm in a certain programming language.

16 1.4 Algorithm Efficiency The efficiency of an algorithm is defined as how efficient this algorithm makes use of the available computer resources. It can be measured by a method called algorithm analysis.